Title :
Reducing state estimation uncertainty through fuzzy logic evaluation of power system measurements
Author :
Holbert, Keith E. ; Lin, Kang
Author_Institution :
Dept. of Electr. Eng., Arizona State Univ., Tempe, AZ
Abstract :
State estimation is widely used for bad data detection and identification. To further insure the validity of measurements from the power system, additional information is incorporated into sensor fault detection and isolation schemes. In particular, we develop a fuzzy logic-based state estimation method that includes data such as historical usage trends and component reliability. Results from applying this hybrid fuzzy classifier system to the IEEE 14-bus test system are presented
Keywords :
fault location; fuzzy logic; power system measurement; power system state estimation; sensors; IEEE 14-bus test system; component reliability; data detection; data identification; fuzzy logic; hybrid fuzzy classifier; isolation scheme; power system measurement; sensor fault detection; state estimation; Electrical fault detection; Fuzzy logic; Fuzzy systems; Hybrid power systems; Power measurement; Power system faults; Power system measurements; Power system reliability; Sensor systems; State estimation;
Conference_Titel :
Probabilistic Methods Applied to Power Systems, 2004 International Conference on
Print_ISBN :
0-9761319-1-9
